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Target margin design through analyzing a large cohort of clinical log data in the cyberknife system
PURPOSE: Calculating the adequate target margin for real‐time tumor tracking using the Cyberknife system is a challenging issue since different sources of error exist. In this study, the clinical log data of the Cyberknife system were analyzed to adequately quantify the planned target volume (PTV) m...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8906228/ https://www.ncbi.nlm.nih.gov/pubmed/35044071 http://dx.doi.org/10.1002/acm2.13476 |
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author | Samadi Miandoab, Payam Saramad, Shahyar Setayeshi, Saeed |
author_facet | Samadi Miandoab, Payam Saramad, Shahyar Setayeshi, Saeed |
author_sort | Samadi Miandoab, Payam |
collection | PubMed |
description | PURPOSE: Calculating the adequate target margin for real‐time tumor tracking using the Cyberknife system is a challenging issue since different sources of error exist. In this study, the clinical log data of the Cyberknife system were analyzed to adequately quantify the planned target volume (PTV) margins of tumors located in the lung and abdomen regions. METHODS: In this study, 45 patients treated with the Cyberknife module were examined. In this context, adequate PTV margins were estimated based on the Van Herk formulation and the uncertainty estimation method by considering the impact of errors and uncertainties. To investigate the impact of errors and uncertainties on the estimated PTV margins, a statistical analysis was also performed. RESULTS: Our study demonstrates five different sources of errors, including segmentation, deformation, correlation, prediction, and targeting errors, which were identified as the main sources of error in the Cyberknife system. Furthermore, the clinical evaluation of the current study reveals that the two different formalisms provided almost identical PTV margin estimates. Additionally, 4–5 mm and 5 mm margins on average could provide adequate PTV margins at lung and abdomen tumors in all three directions, respectively. Overall, it was found that concerning the PTV margins, the impact of correlation and prediction errors is very high, while the impact of robotics error is low. CONCLUSIONS: The current study can address two limitations in previous researches, namely insufficient sample sites and a smaller number of patients. A comparison of the present results concerning the lung and abdomen areas with other studies reveals that the proposed strategy could provide a better reference in selection the PTV margins. To our knowledge, this study is one of the first attempts to estimate the PTV margins in the lung and abdomen regions for a large cohort of patients treated using the Cyberknife system. |
format | Online Article Text |
id | pubmed-8906228 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89062282022-03-10 Target margin design through analyzing a large cohort of clinical log data in the cyberknife system Samadi Miandoab, Payam Saramad, Shahyar Setayeshi, Saeed J Appl Clin Med Phys Radiation Oncology Physics PURPOSE: Calculating the adequate target margin for real‐time tumor tracking using the Cyberknife system is a challenging issue since different sources of error exist. In this study, the clinical log data of the Cyberknife system were analyzed to adequately quantify the planned target volume (PTV) margins of tumors located in the lung and abdomen regions. METHODS: In this study, 45 patients treated with the Cyberknife module were examined. In this context, adequate PTV margins were estimated based on the Van Herk formulation and the uncertainty estimation method by considering the impact of errors and uncertainties. To investigate the impact of errors and uncertainties on the estimated PTV margins, a statistical analysis was also performed. RESULTS: Our study demonstrates five different sources of errors, including segmentation, deformation, correlation, prediction, and targeting errors, which were identified as the main sources of error in the Cyberknife system. Furthermore, the clinical evaluation of the current study reveals that the two different formalisms provided almost identical PTV margin estimates. Additionally, 4–5 mm and 5 mm margins on average could provide adequate PTV margins at lung and abdomen tumors in all three directions, respectively. Overall, it was found that concerning the PTV margins, the impact of correlation and prediction errors is very high, while the impact of robotics error is low. CONCLUSIONS: The current study can address two limitations in previous researches, namely insufficient sample sites and a smaller number of patients. A comparison of the present results concerning the lung and abdomen areas with other studies reveals that the proposed strategy could provide a better reference in selection the PTV margins. To our knowledge, this study is one of the first attempts to estimate the PTV margins in the lung and abdomen regions for a large cohort of patients treated using the Cyberknife system. John Wiley and Sons Inc. 2022-01-19 /pmc/articles/PMC8906228/ /pubmed/35044071 http://dx.doi.org/10.1002/acm2.13476 Text en © 2022 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Radiation Oncology Physics Samadi Miandoab, Payam Saramad, Shahyar Setayeshi, Saeed Target margin design through analyzing a large cohort of clinical log data in the cyberknife system |
title | Target margin design through analyzing a large cohort of clinical log data in the cyberknife system |
title_full | Target margin design through analyzing a large cohort of clinical log data in the cyberknife system |
title_fullStr | Target margin design through analyzing a large cohort of clinical log data in the cyberknife system |
title_full_unstemmed | Target margin design through analyzing a large cohort of clinical log data in the cyberknife system |
title_short | Target margin design through analyzing a large cohort of clinical log data in the cyberknife system |
title_sort | target margin design through analyzing a large cohort of clinical log data in the cyberknife system |
topic | Radiation Oncology Physics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8906228/ https://www.ncbi.nlm.nih.gov/pubmed/35044071 http://dx.doi.org/10.1002/acm2.13476 |
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